Agricultural insurance is an important instrument to protect farmers from risks that can threaten the sustainability of farming, such as crop failure due to natural disasters, pest attacks, and plant diseases. Rice, as a strategic commodity for national food security, is a priority in insurance protection programs. This study aims to calculate rice insurance premiums in West Java Province using the copula method, based on secondary monthly data of rice production and dry grain prices (GKG) from January 2020 to December 2023, as well as daily rainfall data. The methodology includes data exploration, distribution fitting, copula parameter estimation, and premium calculation based on rainfall threshold values. The analysis results indicate that the Gaussian copula is the best model for capturing the dependence between variables, with the lowest AIC and BIC values. Premium calculations based on rainfall indices show variations according to threshold values, with lower premiums for smaller thresholds, confirming the effectiveness of the Gaussian copula in modeling risk for agricultural insurance premiums.
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Sumatera Institute of Technology
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